Evolution and targeting of the functional states of glioblastoma

胶质母细胞瘤功能状态的进化和靶向

• 批准号: 10729932
• 负责人: Antonio Iavarone
• 金额: $ 16.23万
• 依托单位: UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10729932
• 关键词: Evolution; targeting; functional; states; glioblastoma

Project Summary The application is focused on glioblastoma multiforme (GBM), one of the most lethal forms of human cancer for which the massive knowledge generated by genomic data has provided little therapeutic improvement. One key element in the success of clinical studies for cancer patients is the selection of homogeneous groups of patients harboring tumors that share identifiable functional vulnerabilities rather than general biomarkers. In GBM, the lack of a functional classifier has hindered the targeting of fundamental cancer-driving mechanisms in well- defined patient subgroups, leading to discouraging results. The proposal is founded on a novel classification of GBM that we have recently proposed. Different from previously established marker-based classification, the new classifier is centered on functional activities of cancer cells that we identified by single cell transcriptomic analysis. The classifier was validated in several cohorts of bulk primary GBM and includes four subtypes, two linked to neurodevelopmental programs, neuronal and proliferative-progenitor, and two characterized by divergent metabolic activities, mitochondrial and glycolytic-plurimetabolic. Notably, the mitochondrial subtype is endowed with a distinct sensitivity to oxidative phosphorylation inhibition and is associated with a better survival, while the glycolytic-plurimetabolic subtype is characterized by redundant metabolic activities. Our preliminary analysis revealed that each functional GBM subtype is association with biologically coherent proteomic and phosphoproteomic features. In this application we will combine innovative computational tools and state-of-the- art experimental models in vitro and in vivo to study the impact of functional cell states of GBM in therapy resistance. We built the research plan with the following aims: i) examine and target the plasticity of the neurodevelopmental glioma states under therapy pressure and the cross-talk with signals from the microenvironment; ii) determine how mitochondrial cells adjust to therapy pressure when treated with mitochondrial inhibitors and the mechanism of induced resistance; iii) retrieve therapeutic intervention points from proteomic data focusing on DNA-PK and PKCd, two protein kinases active selectively in the proliferative/progenitor and glycolytic/plurimetabolic subtypes of GBM, respectively. Experimental validations will be applied to these nodal factors and will be performed by our laboratories, which in the course of many years have generated and perfected the array of experimental tools including sequence-annotated patient-derived models to pursue each question. By integrating novel computational and experimental platforms to study the evolution of distinct GBM subtypes, the proposal is conceptually and technically innovative. The successful outcome of this proposal will be the delivery of key information to decipher evolving tumor dependencies under treatment and accurate therapeutic strategies specifically tailored to distinct subgroups of GBM patients.

项目摘要 该应用程序的重点是多形性胶质母细胞瘤（GBM），这是人类癌症中最致命的形式之一， 基因组数据产生的大量知识几乎没有提供治疗改进。一个关键 癌症患者临床研究成功的一个要素是选择同质患者组 这些肿瘤具有可识别的功能脆弱性，而不是一般的生物标志物。在GBM中， 缺乏功能性分类器阻碍了对基础癌症驱动机制的靶向， 定义的患者亚组，导致令人沮丧的结果。该建议是建立在一种新的分类基础上的， 我们最近提出的GBM。与以前建立的基于标记的分类不同， 分类器集中在我们通过单细胞转录组学鉴定的癌细胞的功能活性上。 分析.该分类器在几个批量原发性GBM队列中进行了验证，包括四种亚型，两种亚型， 与神经发育程序、神经元和增殖祖细胞有关， 不同的代谢活动，线粒体和糖酵解多代谢。值得注意的是，线粒体亚型是 被赋予对氧化磷酸化抑制的独特敏感性并与更好的存活相关， 而糖酵解-多代谢亚型的特征在于多余的代谢活性。我们的初步 分析显示，每种功能性GBM亚型与生物学相关的蛋白质组学相关， 磷酸化蛋白质组学特征。在这个应用程序中，我们将结合联合收割机创新的计算工具和国家的- 本发明提供了体外和体内实验模型，以研究GBM的功能性细胞状态在治疗中的影响 阻力我们建立了研究计划，目的如下：i）检查和目标的可塑性， 神经发育胶质瘤状态下的治疗压力和串扰的信号， 微环境; ii）确定线粒体细胞如何在用以下药物治疗时适应治疗压力： 线粒体抑制剂和诱导抗性的机制; iii）检索治疗干预点 从蛋白质组学数据集中在DNA-PK和PKCd，两种蛋白激酶活性选择性地在 增殖/祖细胞和糖酵解/多代谢亚型。实验验证将 将应用于这些节点因素，并将由我们的实验室进行，在许多年的过程中， 已经生成并完善了一系列实验工具，包括序列注释的患者衍生的 模型来解决每个问题。通过整合新的计算和实验平台来研究 由于不同GBM亚型的进化，该提案在概念上和技术上都是创新的。成功 该提案的结果将是提供关键信息，以破译肿瘤依赖性的演变， 治疗和准确的治疗策略，专门针对不同亚组的GBM患者。